In this video we build a generative adversarial network based on convolutional neural networks and train it on the CelebA dataset. This is a huge improvement from the previous simple fully connected GAN implemented in previous videos.

DCGAN paper:
https://arxiv.org/abs/1511.06434

CelebA dataset used in video:
https://www.kaggle.com/dataset/504743...

❤️ Support the channel ❤️
   / @aladdinpersson  

Paid Courses I recommend for learning (affiliate links, no extra cost for you):
⭐ Machine Learning Specialization https://bit.ly/3hjTBBt
⭐ Deep Learning Specialization https://bit.ly/3YcUkoI
📘 MLOps Specialization http://bit.ly/3wibaWy
📘 GAN Specialization https://bit.ly/3FmnZDl
📘 NLP Specialization http://bit.ly/3GXoQuP

✨ Free Resources that are great:
NLP: https://web.stanford.edu/class/cs224n/
CV: http://cs231n.stanford.edu/
Deployment: https://fullstackdeeplearning.com/
FastAI: https://www.fast.ai/

💻 My Deep Learning Setup and Recording Setup:
https://www.amazon.com/shop/aladdinpe...

GitHub Repository:
https://github.com/aladdinpersson/Mac...

✅ One-Time Donations:
Paypal: https://bit.ly/3buoRYH

▶️ You Can Connect with me on:
Twitter -   / aladdinpersson  
LinkedIn -   / aladdin-persson-a95384153  
Github - https://github.com/aladdinpersson

OUTLINE:
0:00 - Introduction
0:26 - Quick Paper Recap
4:31 - Implementation of Discriminator
9:38 - Implementation of Generator
15:27 - Weight initialization and test model
19:09 - Setup of training
31:36 - Training on MNIST
32:20 - Modifications to CelebA dataset
33:52 - Training on CelebA and ending